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Federated Learning for Ultra-Reliable Low-Latency V2V Communications

Federated Learning for Ultra-Reliable Low-Latency V2V Communications

11 May 2018
S. Samarakoon
M. Bennis
Walid Saad
Merouane Debbah
ArXiv (abs)PDFHTML

Papers citing "Federated Learning for Ultra-Reliable Low-Latency V2V Communications"

16 / 66 papers shown
Title
Federated Learning with Cooperating Devices: A Consensus Approach for
  Massive IoT Networks
Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks
S. Savazzi
M. Nicoli
V. Rampa
FedML
72
310
0
27 Dec 2019
Advances and Open Problems in Federated Learning
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedMLAI4CE
287
6,329
0
10 Dec 2019
L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient
  Decentralized Deep Learning
L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning
Anis Elgabli
Jihong Park
Sabbir Ahmed
M. Bennis
FedML
75
21
0
09 Nov 2019
Device Scheduling with Fast Convergence for Wireless Federated Learning
Device Scheduling with Fast Convergence for Wireless Federated Learning
Misha Sra
C. Schmandt
Z. Niu
FedML
85
197
0
03 Nov 2019
Experienced Deep Reinforcement Learning with Generative Adversarial
  Networks (GANs) for Model-Free Ultra Reliable Low Latency Communication
Experienced Deep Reinforcement Learning with Generative Adversarial Networks (GANs) for Model-Free Ultra Reliable Low Latency Communication
Ali Taleb
Ieee Walid Saad Fellow
Ieee Mohammad Mozaffari Member
Ieee H. Vincent Poor Fellow
55
91
0
01 Nov 2019
Robust Federated Learning with Noisy Communication
Robust Federated Learning with Noisy Communication
F. Ang
Li Chen
Senior Member Ieee Nan Zhao
Senior Member Ieee Yunfei Chen
Weidong Wang
Feng Yu
FedML
58
117
0
01 Nov 2019
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
Sai Praneeth Karimireddy
Satyen Kale
M. Mohri
Sashank J. Reddi
Sebastian U. Stich
A. Suresh
FedML
75
348
0
14 Oct 2019
Eavesdrop the Composition Proportion of Training Labels in Federated
  Learning
Eavesdrop the Composition Proportion of Training Labels in Federated Learning
Lixu Wang
Shichao Xu
Tianlin Li
Qi Zhu
FedML
83
63
0
14 Oct 2019
From Server-Based to Client-Based Machine Learning: A Comprehensive
  Survey
From Server-Based to Client-Based Machine Learning: A Comprehensive Survey
Renjie Gu
Chaoyue Niu
Fan Wu
Guihai Chen
Chun Hu
Chengfei Lyu
Zhihua Wu
88
26
0
18 Sep 2019
Federated Learning: Challenges, Methods, and Future Directions
Federated Learning: Challenges, Methods, and Future Directions
Tian Li
Anit Kumar Sahu
Ameet Talwalkar
Virginia Smith
FedML
143
4,562
0
21 Aug 2019
Federated Learning for Wireless Communications: Motivation,
  Opportunities and Challenges
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
Solmaz Niknam
Harpreet S. Dhillon
J. H. Reed
75
610
0
30 Jul 2019
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for
  Mobile Crowdsensing
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing
Yang Liu
Zhuo Ma
Ximeng Liu
Siqi Ma
Surya Nepal
R. Deng
FedML
60
63
0
24 Jul 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for
  Data Privacy and Protection
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Yue Liu
Zeyi Wen
Zhaomin Wu
Sixu Hu
Naibo Wang
Yuan N. Li
Xu Liu
Bingsheng He
FedML
130
1,009
0
23 Jul 2019
Astraea: Self-balancing Federated Learning for Improving Classification
  Accuracy of Mobile Deep Learning Applications
Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
Moming Duan
Duo Liu
Xianzhang Chen
Yujuan Tan
Jinting Ren
Lei Qiao
Liang Liang
FedML
66
198
0
02 Jul 2019
Unsupervised Deep Learning for Ultra-reliable and Low-latency
  Communications
Unsupervised Deep Learning for Ultra-reliable and Low-latency Communications
Chengjian Sun
Chenyang Yang
38
15
0
26 Apr 2019
Towards Federated Learning at Scale: System Design
Towards Federated Learning at Scale: System Design
Keith Bonawitz
Hubert Eichner
W. Grieskamp
Dzmitry Huba
A. Ingerman
...
H. B. McMahan
Timon Van Overveldt
David Petrou
Daniel Ramage
Jason Roselander
FedML
128
2,678
0
04 Feb 2019
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